Pricing of Credit Derivatives with and without Counterparty and Collateral Adjustments

Alexander Lipton and David Shelton


Introduction to 'Lessons from the Financial Crisis'


The Credit Crunch of 2007: What Went Wrong? Why? What Lessons Can be Learned?


Underwriting versus Economy: A New Approach to Decomposing Mortgage Losses


The Shadow Banking System and Hyman Minsky’s Economic Journey


The Collapse of the Icelandic Banking System


The Quant Crunch Experience and the Future of Quantitative Investing


No Margin for Error: The Impact of the Credit Crisis on Derivatives Markets


The Re-Emergence of Distressed Exchanges in Corporate Restructurings


Modelling Systemic and Sovereign Risks


Measuring and Managing Risk in Innovative Financial Instruments


Forecasting Extreme Risk of Equity Portfolios with Fundamental Factors


Limits of Implied Credit Correlation Metrics Before and During the Crisis


Another view on the pricing of MBSs, CMOs and CDOs of ABS


Pricing of Credit Derivatives with and without Counterparty and Collateral Adjustments


A Practical Guide to Monte Carlo CVA


The Endogenous Dynamics of Markets: Price Impact, Feedback Loops and Instabilities


Market Panics: Correlation Dynamics, Dispersion and Tails


Financial Complexity and Systemic Stability in Trading Markets


The Martingale Theory of Bubbles: Implications for the Valuation of Derivatives and Detecting Bubbles


Managing through a Crisis: Practical Insights and Lessons Learned for Quantitatively Managed Equity Portfolios


Active Risk Management: A Credit Investor’s Perspective


Investment Strategy Returns: Volatility, Asymmetry, Fat Tails and the Nature of Alpha

Subsequent to the financial crisis of 2007–8, the credit value adjustment (CVA) for derivatives positions (that is, the adjustment to valuation required to account for the credit risk of one or both counter-parties who have entered into a portfolio of transactions) has been an area of heightened focus for banks, regulators and politicians.

In this chapter we will concentrate on the particular case of a portfolio of single name credit default swaps (CDSs). This is a pertinent example since it exhibits so-called “wrong way risk” (Redon 2006); in other words, the size of the exposure is positively correlated with the likelihood of default of the counterparty, as well as being highly asymmetric with respect to the two counterparties. In order to capture this effect, we need to model the default correlation between issuers with a common factor. As we will see, in order to generate significant default correlation it becomes essential to incorporate jumps in this process, representing sudden economy-wide deterioration of credit quality.

Whatever the underlying political motivation for attempting to introduce one or more central clearing counterparties for CDSs, it is clear (Duffie

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